Connecting higher education and renewable energy to attain sustainability for BRICS countries: A climate Kuznets curve perspective

Purpose – Increased trapped heat in the atmosphere leads to global warming and economic activity is the primary culprit. This study proposes the nonlinear impact of economic activity on cooling degree days to develop a climate Kuznets curve (CKC). Further, this study explores the moderating role of higher education and renewable energy in diminishing the climate-altering effects of economic activity.Design/methodology/approach – All the selected BRICS economies range from 1992 to 2020. The CKC analysis uses a distribution and outlier robust panel quantile autoregressive distributed lagged model.Findings – Results confirmed a U-shaped CKC, controlling for population density, renewable energy, tertiary education enrollment and innovation. The moderating role of renewable energy and education can be exploited to tackle the progressively expanding climate challenges. Hence, education and renewable energy intervention can help in reducing CKC-based global warming.Research limitations/implications – This study highlighted the incorporation of climate change mitigating curriculum in education, so that the upcoming economic agents are well equipped to reduce global warming which must be addressed globally.Originality/value – This study is instrumental in developing the climate change-based economic activity Kuznets curve and assessing the potential of higher education and renewable energy policy intervention

A novel method to construct NSSD molecular graphs

A graph is said to be NSSD (=non-singular with a singular deck) if it has no eigenvalue equal to zero, whereas all its vertex-deleted subgraphs have eigenvalues equal to zero. NSSD graphs are of importance in the theory of conductance of organic compounds. In this paper, a novel method is described for constructing NSSD molecular graphs from the commuting graphs of the Hv-group. An algorithm is presented to construct the NSSD graphs from these commuting graphsThis research is partially funded through Quaid-i-Azam University grant URF-201

Toluidine blue: Yet another low cost method for screening oral cavity tumour margins in Third World countries

Objective: To use toluidine blue intra-operatively to identify tumour involved margins after the removal of oral cavity squamous cell carcinoma, and to compare the findings with those of final histopathology.Methods: The study was conducted at the Aga Khan University Hospital from December 1, 2009, to March 14, 2010, and comprised 56 consecutive patients with biopsy-proven squamous cell carcinoma of oral cavity regardless of grade and stage of tumour. Intra-operatively toluidine blue was used on the resected tumour margins and the staining patterns were assessed. Results were then compared with the final histopathology report.Results: A total of 11(19.64%) margins were positive with toluidine blue staining out of which 8 (14.28%) were false positive. Sensitivity and specificity was found to be 100% and 84.9% respectively with a positive predictive value of 27.2%; a negative predictive value of 100%; and diagnostic accuracy of 85.71%.Conclusion: Toluidine blue costs only Rs25 (USD 0.30) and takes only 5 minutes for application and interpretation. It can be used with significant confidence in smaller lesions (T-I and T-II) as an alternative to frozen sections in developing countries where facilities are unavailable. Its use in larger lesions (T-III and TIV) remains the topic of controversy and awaits a multi centre trial with a larger cohort

An Efficient Algorithm for Nontrivial Eigenvectors in Max-Plus Algebra

The eigenproblem for matrices in max-plus algebra describes the steady state of the system, and therefore it has been intensively studied by many authors. In this paper, we propose an algorithm to compute the eigenvalue and the corresponding eigenvectors of a square matrix in an iterative way. The algorithm is extended to compute the nontrivial eigenvectors for Latin squares in max-plus algebra

Trivial and Nontrivial Eigenvectors for Latin Squares in Max-Plus Algebra

A square array whose all rows and columns are different permutations of the same length over the same symbol set is known as a Latin square. A Latin square may or may not be symmetric. For classification and enumeration purposes, symmetric, non-symmetric, conjugate symmetric, and totally symmetric Latin squares play vital roles. This article discusses the Eigenproblem of non-symmetric Latin squares in well known max-plus algebra. By defining a certain vector corresponding to each cycle of a permutation of the Latin square, we characterize and find the Eigenvalue as well as the possible Eigenvectors

An Efficient Algorithm for Eigenvalue Problem of Latin Squares in a Bipartite Min-Max-Plus System

In this paper, we consider the eigenproblems for Latin squares in a bipartite min-max-plus system. The focus is upon developing a new algorithm to compute the eigenvalue and eigenvectors (trivial and non-trivial) for Latin squares in a bipartite min-max-plus system. We illustrate the algorithm using some examples. The proposed algorithm is implemented in MATLAB, using max-plus algebra toolbox. Computationally speaking, our algorithm has a clear advantage over the power algorithm presented by Subiono and van der Woude. Because our algorithm takes 0 . 088783 sec to solve the eigenvalue problem for Latin square presented in Example 2, while the compared one takes 1 . 718662 sec for the same problem. Furthermore, a time complexity comparison is presented, which reveals that the proposed algorithm is less time consuming when compared with some of the existing algorithms

A novel method to construct NSSD molecular graphs

A graph is said to be NSSD (=non-singular with a singular deck) if it has no eigenvalue equal to zero, whereas all its vertex-deleted subgraphs have eigenvalues equal to zero. NSSD graphs are of importance in the theory of conductance of organic compounds. In this paper, a novel method is described for constructing NSSD molecular graphs from the commuting graphs of the Hv-group. An algorithm is presented to construct the NSSD graphs from these commuting graphs